Audio Classification
Transformers
PyTorch
TensorBoard
wav2vec2
Generated from Trainer
Eval Results (legacy)
Instructions to use LBR47/wav2vec2-base-finetuned-gtzan with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LBR47/wav2vec2-base-finetuned-gtzan with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="LBR47/wav2vec2-base-finetuned-gtzan")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("LBR47/wav2vec2-base-finetuned-gtzan") model = AutoModelForAudioClassification.from_pretrained("LBR47/wav2vec2-base-finetuned-gtzan") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fa33605d0f3e5365f19d853159c0ca5b2df81b920c749716d572d6263ca00ae1
- Size of remote file:
- 378 MB
- SHA256:
- 00350513794bf4f21bff34000450f3e448df6786e2f0e25ba4535691c3d90c19
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